Lab05-Image Processing and Analysis

Dr Tran Anh Tuan, University of Science in Math & Computer Faculty

import numpy as np 
import pandas as pd
import cv2 
from matplotlib import pyplot as plt 
import matplotlib.cm as cm
import matplotlib.gridspec as gridspec
from pylab import imread
from skimage.color import rgb2gray

def ShowImage(ImageList, nRows = 1, nCols = 2, WidthSpace = 0.00, HeightSpace = 0.00):
    from matplotlib import pyplot as plt 
    import matplotlib.gridspec as gridspec
    
    gs = gridspec.GridSpec(nRows, nCols)     
    gs.update(wspace=WidthSpace, hspace=HeightSpace) # set the spacing between axes.
    plt.figure(figsize=(20,10))
    for i in range(len(ImageList)):
        ax1 = plt.subplot(gs[i])
        ax1.set_xticklabels([])
        ax1.set_yticklabels([])
        ax1.set_aspect('equal')

        plt.subplot(nRows, nCols,i+1)

        image = ImageList[i].copy()
        if (len(image.shape) < 3):
            plt.imshow(image, plt.cm.gray)
        else:
            plt.imshow(image)
        plt.title("Image " + str(i))
        plt.axis('off')

    plt.show()

discrete_wavelets = ['db5', 'sym5', 'coif5', 'bior1.3', 'haar']
continuous_wavelets = ['mexh', 'morl', 'cgau5', 'gaus5']
 
list_list_wavelets = [discrete_wavelets, continuous_wavelets]
list_funcs = [pywt.Wavelet, pywt.ContinuousWavelet]
 
fig, axarr = plt.subplots(nrows=2, ncols=5, figsize=(16,8))
for ii, list_wavelets in enumerate(list_list_wavelets):
    func = list_funcs[ii]
    row_no = ii
    for col_no, waveletname in enumerate(list_wavelets):
        wavelet = func(waveletname)
        family_name = wavelet.family_name
        biorthogonal = wavelet.biorthogonal
        orthogonal = wavelet.orthogonal
        symmetry = wavelet.symmetry
        if ii == 0:
            _ = wavelet.wavefun()
            wavelet_function = _[0]
            x_values = _[-1]
        else:
            wavelet_function, x_values = wavelet.wavefun()
        if col_no == 0 and ii == 0:
            axarr[row_no, col_no].set_ylabel("Discrete Wavelets", fontsize=16)
        if col_no == 0 and ii == 1:
            axarr[row_no, col_no].set_ylabel("Continuous Wavelets", fontsize=16)
        axarr[row_no, col_no].set_title("{}".format(family_name), fontsize=16)
        axarr[row_no, col_no].plot(x_values, wavelet_function)
        axarr[row_no, col_no].set_yticks([])
        axarr[row_no, col_no].set_yticklabels([])
 
plt.tight_layout()
plt.show()

# Read Image 
image_color = imread("Sample06/church.jpg")
# Convert Image into Gray
image_gray = cv2.cvtColor(image_color, cv2.COLOR_RGB2GRAY)

# Display Image
ShowImage([image_color, image_gray], 1, 2)

import pywt
import pywt.data
from pywt import dwt2, idwt2

# Wavelet transform of image, and plot approximation and details
titles = ['Approximation', ' Horizontal detail',
          'Vertical detail', 'Diagonal detail']
coeffs2 = dwt2(image_gray, discrete_wavelets[3])
LL, (LH, HL, HH) = coeffs2

# Display Image
ShowImage([LL, LH, HL, HH], 2, 2)

cmapList = [cm.gray, cm.jet, cm.rainbow, cm.viridis, cm.cubehelix, cm.RdBu]
fig = plt.figure(figsize=(20,10))
for i, a in enumerate([LL, LH, HL, HH]):
    ax = fig.add_subplot(2, 2, i + 1)
    ax.imshow(a, interpolation="nearest", cmap=cmapList[5])
    ax.set_title(titles[i], fontsize=10)
    ax.set_xticks([])
    ax.set_yticks([])

fig.tight_layout()
plt.show()

# Read Image 
image_color = imread("Sample06/marathon.jpg")
# Convert Image into Gray
image_gray = cv2.cvtColor(image_color, cv2.COLOR_RGB2GRAY)

# Display Image
ShowImage([image_color, image_gray], 1, 2)

from pywt._doc_utils import wavedec2_keys, draw_2d_wp_basis

x = image_gray.astype(np.float32)
shape = x.shape


max_lev = 3       # how many levels of decomposition to draw
label_levels = 3  # how many levels to explicitly label on the plots

fig, axes = plt.subplots(2, 4, figsize=[14, 8])
for level in range(0, max_lev + 1):
    if level == 0:
        # show the original image before decomposition
        axes[0, 0].set_axis_off()
        axes[1, 0].imshow(x, cmap=plt.cm.gray)
        axes[1, 0].set_title('Image')
        axes[1, 0].set_axis_off()
        continue

    # plot subband boundaries of a standard DWT basis
    draw_2d_wp_basis(shape, wavedec2_keys(level), ax=axes[0, level],
                     label_levels=label_levels)
    axes[0, level].set_title('{} level\ndecomposition'.format(level))

    # compute the 2D DWT
    c = pywt.wavedec2(x, 'db2', mode='periodization', level=level)
    # normalize each coefficient array independently for better visibility
    c[0] /= np.abs(c[0]).max()
    for detail_level in range(level):
        c[detail_level + 1] = [d/np.abs(d).max() for d in c[detail_level + 1]]
    # show the normalized coefficients
    arr, slices = pywt.coeffs_to_array(c)
    axes[1, level].imshow(arr, cmap=plt.cm.gray)
    axes[1, level].set_title('Coefficients\n({} level)'.format(level))
    axes[1, level].set_axis_off()

plt.tight_layout()
plt.show()

# Read Image 
image_color = imread("Sample06/drawing.jpg")
# Convert Image into Gray
image_gray = cv2.cvtColor(image_color, cv2.COLOR_RGB2GRAY)

# Display Image
ShowImage([image_color, image_gray], 1, 2)

coeffs2 = dwt2(image_gray, discrete_wavelets[4])  
LL, (LH, HL, HH) = coeffs2

# Display Image
ShowImage([LL, LH, HL, HH], 2, 2)

cmapList = [cm.gray, cm.jet, cm.rainbow, cm.viridis, cm.cubehelix, cm.RdBu]
fig = plt.figure(figsize=(20,10))
for i, a in enumerate([LL, LH, HL, HH]):
    ax = fig.add_subplot(2, 2, i + 1)
    ax.imshow(a, interpolation="nearest", cmap=cmapList[5])
    ax.set_title(titles[i], fontsize=10)
    ax.set_xticks([])
    ax.set_yticks([])

fig.tight_layout()
plt.show()